Field of the Invention
The present invention relates to a clinical information processing apparatus and method for calculating a degree of similarity between a case of a target patient and a case of a comparison target patient. Further, the present invention relates to a program for causing a computer to execute the clinical information processing method.
Description of the Related Art
In recent years, in medical fields, diagnosis assistance techniques utilizing various kinds of information obtained in examination and treatment of patients drew attention. Further, a technique for extracting, as reference information for diagnosing a disease name or determining a treatment policy of a target patient, a past case of a comparison target patient similar to a target patient's case is expected. The similar case of the comparison target patient is extracted by calculating degrees of similarity between the target patient's case and cases of comparison target patients based on various clinical-information items included in each case of past patients.
Japanese Unexamined Patent Publication No. 2003-122845 (Patent Document 1) proposes a method in which symptoms of a retrieval target case are input as a symptom list. Further, the input symptom list is converted into a symptom vector based on a criterion, such as presence and the grade of a symptom. Further, a degree of similarity between the symptom vector of the retrieval target and a symptom vector of each symptom registered in a symptom information database is calculated based on a total number of symptoms in which the two symptom vectors coincide with each other.
U.S. Patent Application Publication No. 20040193022 (Patent Document 2) proposes a method in which a degree of similarity of each case data to new patient data is calculated when the new patient data are input. The degree of similarity is calculated, as a sum of value groups obtained by weighting a difference between a value of case data and a value of the new patient data for each item based on the degree of influence of the value of the item in the new patient data. Further, a degree of similarity of each disease name is obtained as a sum of degrees of similarity of case data having the disease name, and a disease name in which the degree of similarity is the highest is displayed together with a value of an item in the new patient data used in calculation of the degree of similarity, and the degree of influence of which is the highest.
However, since there are various kinds of clinical-information items, and symptoms include the clinical-information items in various combinations, there are so many kinds of symptoms. Therefore, when symptom data managed by each hospital or the like are arranged for each disease name or the like, the number of cases for each disease name often tends to be small. With respect to clinical-information items, the method disclosed in Patent Document 1 can evaluate, as a case of a high degree of similarity, a case in which most of information coincides if such a case exists. However, since weighting on each symptom is not considered, if only cases in which information slightly coincides exist, it is impossible to appropriately evaluate the degree of similarity.
Meanwhile, the method disclosed in Patent Document 2 calculates a degree of similarity based on a probability (a conditional probability) of belonging to each disease name when each clinical-information item, such as an age, belongs to a predetermined value. The method calculates the degree of similarity based on the degree of influence for judging a disease name for each clinical-information item and information about a difference between a value of case data and a value of the new patient data. However, in the method of Patent Document 2, the degree of influence of each clinical-information item is the same regardless of the disease name. Therefore, it is impossible to accurately calculate a degree of similarity based on the characteristic of each clinical-information item. Further, with respect to values of various clinical-information items, it is not always appropriate to simply evaluate a degree of similarity only based on a difference between values of clinical-information items of case data and those of new patient data. It is not appropriate to evaluate the degree of similarity in such a manner when it is important to judge whether the value of a clinical-information item belongs to a standard range that is considered to be normal in medical diagnosis, or when values of the clinical-information items change nonlinearly. Therefore, the degree of similarity calculated by using the method disclosed in Patent Document 2 is not accurate, and the method is not practical.